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Don't Take the Premise for Granted: Mitigating Artifacts in Natural
  Language Inference

Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference

9 July 2019
Yonatan Belinkov
Adam Poliak
Stuart M. Shieber
Benjamin Van Durme
Alexander M. Rush
ArXivPDFHTML

Papers citing "Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference"

27 / 27 papers shown
Title
ANPMI: Assessing the True Comprehension Capabilities of LLMs for Multiple Choice Questions
ANPMI: Assessing the True Comprehension Capabilities of LLMs for Multiple Choice Questions
Gyeongje Cho
Yeonkyoung So
Jaejin Lee
ELM
62
0
0
26 Feb 2025
SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases
SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases
Yanchen Liu
Jing Yang
Yan Chen
Jing Liu
Huaqin Wu
MoE
47
2
0
28 Feb 2023
Backdoor Learning for NLP: Recent Advances, Challenges, and Future
  Research Directions
Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions
Marwan Omar
SILM
AAML
33
20
0
14 Feb 2023
DISCO: Distilling Counterfactuals with Large Language Models
DISCO: Distilling Counterfactuals with Large Language Models
Zeming Chen
Qiyue Gao
Antoine Bosselut
Ashish Sabharwal
Kyle Richardson
34
25
0
20 Dec 2022
Feature-Level Debiased Natural Language Understanding
Feature-Level Debiased Natural Language Understanding
Yougang Lyu
Piji Li
Yechang Yang
Maarten de Rijke
Pengjie Ren
Yukun Zhao
Dawei Yin
Z. Ren
32
10
0
11 Dec 2022
Looking at the Overlooked: An Analysis on the Word-Overlap Bias in
  Natural Language Inference
Looking at the Overlooked: An Analysis on the Word-Overlap Bias in Natural Language Inference
S. Rajaee
Yadollah Yaghoobzadeh
Mohammad Taher Pilehvar
36
5
0
07 Nov 2022
Towards Robust Visual Question Answering: Making the Most of Biased
  Samples via Contrastive Learning
Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive Learning
Q. Si
Yuanxin Liu
Fandong Meng
Zheng Lin
Peng Fu
Yanan Cao
Weiping Wang
Jie Zhou
37
23
0
10 Oct 2022
Distilling Model Failures as Directions in Latent Space
Distilling Model Failures as Directions in Latent Space
Saachi Jain
Hannah Lawrence
Ankur Moitra
A. Madry
23
90
0
29 Jun 2022
Learning to Split for Automatic Bias Detection
Learning to Split for Automatic Bias Detection
Yujia Bao
Regina Barzilay
17
20
0
28 Apr 2022
Generating Data to Mitigate Spurious Correlations in Natural Language
  Inference Datasets
Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets
Yuxiang Wu
Matt Gardner
Pontus Stenetorp
Pradeep Dasigi
31
67
0
24 Mar 2022
Counterfactual Samples Synthesizing and Training for Robust Visual
  Question Answering
Counterfactual Samples Synthesizing and Training for Robust Visual Question Answering
Long Chen
Yuhang Zheng
Yulei Niu
Hanwang Zhang
Jun Xiao
AAML
OOD
18
36
0
03 Oct 2021
Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense
  Language Understanding
Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understanding
Shane Storks
Qiaozi Gao
Yichi Zhang
J. Chai
ReLM
LRM
47
22
0
10 Sep 2021
Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot
  Event Classification
Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot Event Classification
Peiyi Wang
Runxin Xu
Tianyu Liu
Damai Dai
Baobao Chang
Zhifang Sui
27
16
0
29 Aug 2021
An Investigation of the (In)effectiveness of Counterfactually Augmented
  Data
An Investigation of the (In)effectiveness of Counterfactually Augmented Data
Nitish Joshi
He He
OODD
19
46
0
01 Jul 2021
Learning Stable Classifiers by Transferring Unstable Features
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao
Shiyu Chang
Regina Barzilay
OOD
27
8
0
15 Jun 2021
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao
Shiyu Chang
Regina Barzilay
11
20
0
26 May 2021
Supervising Model Attention with Human Explanations for Robust Natural
  Language Inference
Supervising Model Attention with Human Explanations for Robust Natural Language Inference
Joe Stacey
Yonatan Belinkov
Marek Rei
30
45
0
16 Apr 2021
SILT: Efficient transformer training for inter-lingual inference
SILT: Efficient transformer training for inter-lingual inference
Javier Huertas-Tato
Alejandro Martín
David Camacho
27
11
0
17 Mar 2021
DynaSent: A Dynamic Benchmark for Sentiment Analysis
DynaSent: A Dynamic Benchmark for Sentiment Analysis
Christopher Potts
Zhengxuan Wu
Atticus Geiger
Douwe Kiela
230
77
0
30 Dec 2020
Explaining Deep Neural Networks
Explaining Deep Neural Networks
Oana-Maria Camburu
XAI
FAtt
28
26
0
04 Oct 2020
The Sensitivity of Language Models and Humans to Winograd Schema
  Perturbations
The Sensitivity of Language Models and Humans to Winograd Schema Perturbations
Mostafa Abdou
Vinit Ravishankar
Maria Barrett
Yonatan Belinkov
Desmond Elliott
Anders Søgaard
ReLM
LRM
62
34
0
04 May 2020
HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in
  Natural Language Inference
HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference
Tianyu Liu
Xin Zheng
Baobao Chang
Zhifang Sui
43
23
0
05 Mar 2020
Adversarial Filters of Dataset Biases
Adversarial Filters of Dataset Biases
Ronan Le Bras
Swabha Swayamdipta
Chandra Bhagavatula
Rowan Zellers
Matthew E. Peters
Ashish Sabharwal
Yejin Choi
36
220
0
10 Feb 2020
Recent Advances in Natural Language Inference: A Survey of Benchmarks,
  Resources, and Approaches
Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches
Shane Storks
Qiaozi Gao
J. Chai
21
128
0
02 Apr 2019
Hypothesis Only Baselines in Natural Language Inference
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak
Jason Naradowsky
Aparajita Haldar
Rachel Rudinger
Benjamin Van Durme
190
576
0
02 May 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
297
6,959
0
20 Apr 2018
A Decomposable Attention Model for Natural Language Inference
A Decomposable Attention Model for Natural Language Inference
Ankur P. Parikh
Oscar Täckström
Dipanjan Das
Jakob Uszkoreit
210
1,367
0
06 Jun 2016
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